Early-Season Crop Mapping on an Agricultural Area in Italy Using <italic>X</italic>-Band Dual-Polarization SAR Satellite Data and Convolutional Neural Networks

Early-Season Crop Mapping on an Agricultural Area in Italy Using <italic>X</italic>-Band Dual-Polarization SAR Satellite Data and Convolutional Neural Networks

Early-season crop mapping provides decision-makers with timely information on crop types and conditions that are crucial for agricultural management. Current satellite-based mapping solutions mainly rely on optical imagery, albeit limited by weather conditions. Very few exploit long-time series of p...

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Bibliographic Details
Main Authors: Giacomo Fontanelli, Alessandro Lapini, Leonardo Santurri, Simone Pettinato, Emanuele Santi, Giuliano Ramat, Simone Pilia, Fabrizio Baroni, Deodato Tapete, Francesca Cigna, Simonetta Paloscia
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Convolutional neural network (CNN)
COSMO-SkyMed
crop early mapping
deep learning
dual polarization
synthetic aperture radar (SAR)
Online Access:https://ieeexplore.ieee.org/document/9864054/

Internet

https://ieeexplore.ieee.org/document/9864054/

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